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At least 289 records · Page 16

The Evolution of AGN Activity in Brightest Cluster Galaxies

We present the results of an analysis of Wide-field Infrared Survey Explorer (WISE) observations of the full 2500 deg 2 South Pole Telescope (SPT)-Sunyaev–Zel'dovich cluster sample. We describe a process for identifying active galactic nuclei (AGN) in brightest cluster galaxies (BCGs) based on WISE mid-IR color and redshift. Applying this technique to the BCGs of the SPT-SZ sample, we calculate the AGN-hosting BCG fraction, which is defined as the fraction of BCGs hosting bright central AGNs over all possible BCGs. Assuming an evolving single-burst stellar population model, we find statistically significant evidence (>99.9%) for a mid-IR excess at high redshift compared to low redshift, suggesting that the fraction of AGN-hosting BCGs increases with redshift over the range of 0 < z < 1.3. The best-fit redshift trend of the AGN-hosting BCG fraction has the form (1 + z) 4.1±1.0 . These results are consistent with previous studies in galaxy clusters as well as as in field galaxies. One way to explain this result is that member galaxies at high redshift tend to have more cold gas. While BCGs in nearby galaxy clusters grow mostly by dry mergers with cluster members, leading to no increase in AGN activity, BCGs at high redshift could primarily merge with gas-rich satellites, providing fuel for feeding AGNs. If this observed increase in AGN activity is linked to gas-rich mergers rather than ICM cooling, we would expect to see an increase in scatter in the P cav versus L cool relation at z > 1. Last, this work confirms that the runaway cooling phase, as predicted by the classical cooling-flow model, in the Phoenix cluster is extremely rare and most BCGs have low (relative to Eddington) black hole accretion rates.

79 ASTRONOMY AND ASTROPHYSICS↗

Compact Steep Spectrum Radio Sources with Enhanced Star Formation Are Smaller Than 10 kpc

Compact steep spectrum (CSS) radio sources are active galactic nuclei (AGN) that have radio jets propagating only on galactic scales, defined as having projected linear size (LS) of up to 20 kpc. CSS sources are generally hosted by massive early-type galaxies with little ongoing star formation; however, a small fraction are known to have enhanced star formation. Using archival data from the Faint Images of the Radio Sky at Twenty cm survey, the Very Large Array Sky Survey, and the Sloan Digital Sky Survey, we identify a volume-limited sample of 166 CSS sources at z < 0.2 with L 1.4 GHz > 10 24 W Hz -1 . Comparing the star formation rates and linear sizes of these CSS sources, we find that the ≈14% of CSS sources with specific star formation rates above 0.01 Gyr -1 all have LS < 10 kpc. We discuss the possible mechanisms driving this result, concluding that it is likely the excess star formation in these sources occurred in multiple bursts and ceased prior to the AGN jet being triggered.

79 ASTRONOMY AND ASTROPHYSICS↗

A prediction interval method for uncertainty quantification of regression models

This paper considers calculation of prediction intervals (PIs) by neural networks (NNs) for quantifying uncertainty in regression tasks, so as to provide fast, accurate and robust emulators to accelerate scientific simulations. We propose a novel method to learn lower and upper bounds of the PI using independent NNs without defining an exclusive loss. Our method requires no distributional assumption, does not introduce extra hyper-parameters, and can effectively identify out-of-distribution samples and quantify their uncertainty. We demonstrate advantages of our method using a benchmark problem and two real-world scientific applications.

Zhang, Pei↗

Function-based probes for environmental microbiome analysis and methods of making and using the same

Probe embodiments for identifying analytes involved in biofuel or bioenergy production, bioremediation, or nutrient cycling as well as methods of making and use are described herein. In some embodiments, probes identifying cellulose degradation and/or sugar transport, lignin or chitin degradation, or peptide or toxin metabolism are included. In some embodiments, probes for identifying analytes in a soil sample are included in the compositions and methods disclosed herein.

Wright, Aaron T.↗

Creating Accurate Methane Emission Inventories through Data-Driven Airborne Survey Strategies: Methods and Results from the Haynesville, Anadarko, and Permian Basins

Significantly reducing methane emissions from the oil and gas sector can decrease the rate of climate change over the next two decades, buying critical time for a global energy transition. However, emissions inventories that can be used by oil and gas operators and environmental regulators to identify optimal methane emission mitigation strategies are either based on conservative emission factor methods, or are inconsistent between studies due to differences in sampling strategies or survey technologies. We developed a new approach for methane emissions survey design that yields representative basinwide methane emissions inventories by surveying a subset of total assets in a given oil and gas basin. We identify several sampling and analysis principles, including large sample sizes, balanced sampling across oil and gas production, careful survey area definition, and a unified protocol for analysis, to be vital to producing an unbiased estimate of basin-scale emissions that can be reconciled with future studies. We further present results from deploying this strategy in two oil and gas producing regions in the United States: the Haynesville Basin in Texas and Louisiana, and the Woodford Shale in the Anadarko Basin in Oklahoma. Aerial surveys were performed in 2023 using the Insight M LeakSurveyor™ technology. Preliminary results from methane emissions detected by Insight M indicate that aerially detected emissions above roughly 30 kg(CH4)/hr by themselves contribute a fractional loss rate of 1.13% of gross gas production across oil and gas operations in the Haynesville Basin, with aerially detected emissions equivalent to 2.67% of gross gas production in the Woodford Shale. We supplement these aerial estimates with modeled emissions that are below the LeakSurveyor’s survey sensitivity using a recently published inventory-based model of methane emissions, which we update for our survey areas. We then combine our aerial detections with modeled emissions to yield methane emission distributions and inventories that incorporate the full range of potential methane emissions from the smallest to the largest. These results can be used to identify the most effective methane mitigation strategies for our study areas, and can be reconciled with future methane emissions surveys that use different technologies.

Sherwin, Evan (ORCID:0000000321804297)↗

X-ray properties of the X-CLASS-redMaPPer galaxy cluster sample: the luminosity–temperature relation

ABSTRACT This article presents the results of a spectroscopic analysis of the X-CLASS-redMaPPer (XC1-RM) galaxy cluster sample. X-CLASS is a serendipitous search for clusters in X-ray wavebands based on the XMM–Newton archive, whereas redMaPPer is an optical cluster catalogue derived from the Sloan Digital Sky Survey (SDSS). The present sample comprises 92 X-ray extended sources identified in optical images within 1 arcmin separation. The area covered by the cluster sample is ∼ 27 deg2. The clusters span a wide redshift range (0.05 < z < 0.6) and 88 clusters benefit from spectrosopically confirmed redshifts using data from SDSS Data Release 14. We present an automated pipeline to derive the X-ray properties of the clusters in three distinct apertures: R500 (at fixed mass overdensity), Rfit (at fixed signal-to-noise ratio) and ${R}_{300\, {\rm kpc}}$ (fixed physical radius). The sample extends over wide temperature and luminosity ranges: from 1–10 keV and from 6 × 1042 to 11 × 1044 erg s−1, respectively. We investigate the luminosity–temperature (L–T) relation of the XC1-RM sample and find a slope equal to 3.03 ± 0.26. It is steeper than predicted by self-similar assumptions, in agreement with independent studies. A simplified approach is developed to estimate the amount and impact of selection biases that might be affecting our recoveredL–Tparameters. The result of this simulation process suggests that the measuredL–Trelation is biased to a steeper slope and higher normalization.

Molham, Mona↗

Autoregressive neural quantum states of Fermi Hubbard models

Neural quantum states (NQSs) have emerged as a powerful ansatz for variational quantum Monte Carlo studies of strongly correlated systems. Here, we apply recurrent neural networks (RNNs) and autoregressive transformer neural networks to the Fermi-Hubbard and the (non-Hermitian) Hatano-Nelson-Hubbard models in one and two dimensions. In both cases, we observe that the convergence of the RNN ansatz is challenged when increasing the interaction strength. We present a physically motivated and easy-to-implement strategy for improving the optimization, namely, by ramping of the model parameters. Furthermore, we investigate the advantages and disadvantages of the autoregressive sampling property of both network architectures. For the Hatano-Nelson-Hubbard model, we identify convergence issues that stem from the autoregressive sampling scheme in combination with the non-Hermitian nature of the model. Our findings provide insights into the challenges of the NQS approach and make the first step towards exploring strongly correlated electrons using this ansatz. Published by the American Physical Society 2025

Ibarra-García-Padilla, Eduardo (ORCID:000000019165↗

The SDSS/APOGEE catalogue of HgMn stars

ABSTRACT We report on H-band spectra of chemically peculiar Mercury–Manganese (HgMn) stars obtained via the SDSS/APOGEE survey. As opposed to other varieties of chemically peculiar stars such as classical Ap/Bp stars, HgMn stars lack strong magnetic fields and are defined by extreme overabundances of Mn, Hg, and other heavy elements. A satisfactory explanation for the abundance patterns remains to be determined, but low rotational velocity is a requirement and involvement in binary/multiple systems may be as well. The APOGEE HgMn sample currently consists of 269 stars that were identified among the telluric standard stars as those whose metallic absorption content is limited to or dominated by the H-band Mn ii lines. Due to the fainter magnitudes probed by the APOGEE survey as compared to past studies, only 9/269 stars in the sample were previously known as HgMn types. The 260 newly identified HgMn stars represents a more than doubling of the known sample. At least 32 per cent of the APOGEE sample are found to be binary or multiple systems, and from multi-epoch spectroscopy, we were able to determine orbital solutions for at least one component in 32 binaries. Many of the multilined systems include chemically peculiar companions, with noteworthy examples being the HgMn+Ap/Bp binary HD 5429, the HgMn+HgMn binary HD 298641, and the HgMn+Bp Mn + Am triple system HD 231263. As a further peculiarity, roughly half of the sample produces narrow emission in the C i 16895 Å line, with widths and radial velocities that match those of the Mn ii lines.

Chojnowski, S. Drew↗

Identification of dislocation-related and point-defects in III-As layers for silicon photonics applications

Abstract The aim of this paper is to identify, analyze and compare the defects present in III-As, as a function of dislocation density, and as a function of the presence/absence of quantum dots (QDs). Such materials are of fundamental importance for the development of lasers and photodiodes for silicon photonics. The study is based on an extensive deep-level transient spectroscopy investigation, carried out on GaAs pin diodes grown on Si and on GaAs (that differ in the dislocation density), with and without embedded QDs. The original results described in this paper demonstrate that: (a) we were able to identify four different defects within the device grown on Si (three electron and one hole traps) and one defect (hole trap) in the device on GaAs, common to both samples; (b) all the majority carrier traps identified are located near midgap, i.e. are efficient non-radiative recombination centers; (c) such defects are absent (or non-detectable) in the sample grown on GaAs substrate, having a very low dislocation density; (d) the presence of QDs does not result in additional defects within the semiconductor material; (e) the analysis of the capture kinetics revealed that two of the identified traps are related to point defects, whereas the other two traps can be associated with point defects located near a dislocation; (f) a comparison with previous reports indicate that the detected traps are related to native III-As defects, or to oxygen-related complexes.

Physics↗

Mafic explosive volcanism at Llaima Volcano: 3D x-ray microtomography reconstruction of pyroclasts to constrain shallow conduit processes

Abstract Mafic volcanic activity is dominated by effusive to mildly explosive eruptions. Plinian and ignimbrite-forming mafic eruptions, while rare, are also possible; however, the conditions that promote such explosivity are still being explored. Eruption style is determined by the ability of gas to escape as magma ascends, which tends to be easier in low-viscosity, mafic magmas. If magma permeability is sufficiently high to reduce bubble overpressure during ascent, volatiles may escape from the magma, inhibiting violent explosive activity. In contrast, if the permeability is sufficiently low to retain the gas phase within the magma during ascent, bubble overpressure may drive magma fragmentation. Rapid ascent may induce disequilibrium crystallization, increasing viscosity and affecting the bubble network with consequences for permeability, and hence, explosivity. To explore the conditions that promote strongly explosive mafic volcanism, we combine microlite textural analyses with synchrotron x-ray computed microtomography of 10 pyroclasts from the 12.6 ka mafic Curacautín Ignimbrite (Llaima Volcano, Chile). We quantify microlite crystal size distributions (CSD), microlite number densities, porosity, bubble interconnectivity, bubble number density, and geometrical properties of the porous media to investigate the role of magma degassing processes at mafic explosive eruptions. We use an analytical technique to estimate permeability and tortuosity by combing the Kozeny-Carman relationship, tortuosity factor, and pyroclast vesicle textures. The groundmass of our samples is composed of up to 44% plagioclase microlites, > 85% of which are < 10 µm in length. In addition, we identify two populations of vesicles in our samples: (1) a convoluted interconnected vesicle network produced by extensive coalescence of smaller vesicles (> 99% of pore volume), and (2) a population of very small and completely isolated vesicles (< 1% of porosity). Computed permeability ranges from 3.0 × 10 −13 to 6.3 × 10 −12 m 2 , which are lower than the similarly explosive mafic eruptions of Tarawera (1886; New Zealand) and Etna (112 BC; Italy). The combination of our CSDs, microlite number densities, and 3D vesicle textures evidence rapid ascent that induced high disequilibrium conditions, promoting rapid syn-eruptive crystallization of microlites within the shallow conduit. We interpret that microlite crystallization increased viscosity while simultaneously forcing bubbles to deform as they grew together, resulting in the permeable by highly tortuous network of vesicles. Using the bubble number densities for the isolated vesicles (0.1-3 −3 × 10 4 bubbles per mm 3 ), we obtain a minimum average decompression rate of 1.4 MPa/s. Despite the textural evidence that the Curacautín magma reached the percolation threshold, we propose that rapid ascent suppressed outgassing and increased bubble overpressures, leading to explosive fragmentation. Further, using the porosity and permeability of our samples, we estimated that a bubble overpressure > 5 MPa could have been sufficient to fragment the Curacautín magma. Other mafic explosive eruptions report similar disequilibrium conditions induced by rapid ascent rate, implying that syn-eruptive disequilibrium conditions may control the explosivity of mafic eruptions more generally.

Valdivia, Pedro↗

Technical Guidance on Use of the Netzsch LFA 447 Nanoflash for Measurement of Ceramic-Metallic (Cermet) Pellet Specimen

The Netzsch LFA 447 Nanoflash Instrument uses the laser flash method to measure thermal diffusivity of a material. Thermal conductivity can be determined if specific heat and density are known for that material. The 238 Pu Supply Program is interested in re-establishing the capability to determine thermal diffusivity and thermal conductivity of various 237Np Al/cermet samples during heating. The bottom side of a plane parallel sample is heated by an energy pulse from a light source (in this case a xenon lamp). An infrared (IR) detector is on the top side of the sample which detects the time dependent temperature rise of the sample due to the energy input from the xenon lamp. The LFA 447 Nanoflash is user-friendly, simple to operate, and has minor sample preparation which will allow technicians to be trained easily on its use. When using the multi-property measurement option, the LFA 447 Nanoflash can determine both thermal diffusivity and specific heat which means only density is needed to identify the thermal conductivity of a sample. This equipment is recognized for being highly accurate and having fast test times, replacing steady-state methods which have proven to be difficult and much slower.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Limits of Detection for EXAFS Characterization of Heterogeneous Single-Atom Catalysts

Single-atom catalysts (SACs), consisting of individual metal atoms dispersed on a support, attract attention due to their unique reactivity, efficient use of precious metals, and precise chemical tunability. Characterization of the metal species is crucial to substantiate structure–function relationships. Authors often use—and referees often require—X-ray absorption spectroscopy (XAS) data to prove the absence of clustered metal (or metal oxide) structures after pre-treatment and under in situ or operando conditions. However, there has been no critical assessment of the limitations of XAS in substantiating such conclusive statements, which is particularly important given the potential outsized influence of minority catalyst structures in dictating catalytic activity. Here, in this article, we quantitatively assess the detection limits of XAS to identify metal (or metal oxide) clusters in samples containing predominantly single atoms by modeling the extended X-ray absorption fine structure (EXAFS) of mixtures of structures. We identified that a significant fraction of clusters can coexist with SAC active sites (e.g., ~10% metallic Pt or ~40% oxidized Pt clusters in Pt/CeO 2 SACs), while eluding detection via EXAFS with any statistical significance. To generalize these conclusions, a descriptor-based screening of bulk metal oxides using a continuous Cauchy wavelet transform was proposed that suggests certain materials for which differentiating atomically dispersed metal species and metal oxide clusters would be infeasible by EXAFS (e.g., ReO x ). Based on this analysis, we suggest best practices for the study of SACs using EXAFS and provide recommendations to ensure that conclusions do not outpace the evidence used to support them. In this rapidly expanding research area, rigorous characterization will lead to greater understanding of the behavior of SACs and ultimately improved catalytic materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Comprehensive Urine Proteome Database Generated From Patients With Various Renal Conditions and Prostate Cancer

Urine proteins can serve as viable biomarkers for diagnosing and monitoring various diseases. A comprehensive urine proteome database, generated from a variety of urine samples with different disease conditions, can serve as a reference resource for facilitating discovery of potential urine protein biomarkers. Herein, we present a urine proteome database generated from multiple datasets using 2D LC-MS/MS proteome profiling of urine samples from healthy individuals (HI), renal transplant patients with acute rejection (AR) and stable graft (STA), patients with non-specific proteinuria (NS), and patients with prostate cancer (PC). A total of ~28,000 unique peptides spanning ~2,200 unique proteins were identified with a false discovery rate of <0.5% at the protein level. Over one third of the annotated proteins were plasma membrane proteins and another one third were extracellular proteins according to gene ontology analysis. Ingenuity Pathway Analysis of these proteins revealed 349 potential biomarkers in the literature-curated database. Forty-three percentage of all known cluster of differentiation (CD) proteins were identified in the various human urine samples. Interestingly, following comparisons with five recently published urine proteome profiling studies, which applied similar approaches, there are still ~400 proteins which are unique to this current study. These may represent potential disease-associated proteins. Among them, several proteins such as serpin B3, renin receptor, and periostin have been reported as pathological markers for renal failure and prostate cancer, respectively. Taken together, our data should provide valuable information for future discovery and validation studies of urine protein biomarkers for various diseases.

60 APPLIED LIFE SCIENCES↗

Foot-and-Mouth Disease Virus Interserotypic Recombination in Superinfected Carrier Cattle

Viral recombination contributes to the emergence of novel strains with the potential for altered host range, transmissibility, virulence, and immune evasion. For foot-and-mouth disease virus (FMDV), cell culture experiments and phylogenetic analyses of field samples have demonstrated the occurrence of recombination. However, the frequency of recombination and associated virus–host interactions within an infected host have not been determined. We have previously reported the detection of interserotypic recombinant FMDVs in oropharyngeal fluid (OPF) samples of 42% (5/12) of heterologously superinfected FMDV carrier cattle. The present investigation consists of a detailed analysis of the virus populations in these samples including identification and characterization of additional interserotypic minority recombinants. In every animal in which recombination was detected, recombinant viruses were identified in the OPF at the earliest sampling point after superinfection. Some recombinants remained dominant until the end of the experiment, whereas others were outcompeted by parental strains. Genomic analysis of detected recombinants suggests host immune pressure as a major driver of recombinant emergence as all recombinants had capsid-coding regions derived from the superinfecting virus to which the animals did not have detectable antibodies at the time of infection. In vitro analysis of a plaque-purified recombinant virus demonstrated a growth rate comparable to its parental precursors, and measurement of its specific infectivity suggested that the recombinant virus incurred no penalty in packaging its new chimeric genome. These findings have important implications for the potential role of persistently infected carriers in FMDV ecology and the emergence of novel strains.

59 BASIC BIOLOGICAL SCIENCES↗

Krypton-85 chronometry of spent nuclear fuel

We describe the use of the radionuclide 85 Kr, which is produced by nuclear fission and has a half-life of 10.76 years, to determine the age of spent nuclear fuel. The method is based on mass-spectrometric measurement of the relative abundance of fissiogenic Kr isotopes extracted from a fuel sample, and we show that it can be applied to micron-scale particles of spent fuel that are analogous to particles that have been released into the environment from various nuclear facilities in the past. 85 Kr chronometry is potentially valuable for identifying and attributing nuclear materials, grouping samples into collections of common origin that can be used to reconstruct the origin and irradiation history of the material, and verifying declared nuclear activities in the context of international monitoring programs.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Genomic-based biosurveillance for avian influenza: whole genome sequencing from wild mallards sampled during autumn migration in 2022–2023 reveals a high co-infection rate on migration stopover site in Georgia

The Caucasus region, including Georgia, is an important intersection for migratory waterbirds, offering potential for avian influenza virus (AIV) transmission between populations from different geographic areas. In 2022 and 2023, wild ducks were sampled during autumn migration events in Georgia to study the genetic relationships and molecular characteristics of influenza strains. Sequencing and phylogenetic analysis were used to compare the sampled strains to reference sequences from Africa, Asia, and Europe, allowing assessment of genetic relationships and virus transmission between migratory birds. Protein language modeling identified potential co-infections. Of 225 duck samples, 128 tested positive for the influenza M gene. 55 influenza-positive samples underwent whole-genome sequencing, revealing significant diversity. Analysis of the hemagglutinin (HA) segment showed notable differences among subtypes. Most samples were H6N1 and H6N6, but co-infections with combinations like H6H3, N8N1, N6H9, N2N6, and H9H6/N1N2 were also identified. These findings demonstrate the high variability of influenza viruses in migratory waterbirds in Georgia, including a notable rate of co-infections. Some samples exhibited uncommon genetic characteristics compared to other strains from the same year, suggesting Georgia’s role as a mixing vessel for influenza viruses. This facilitates reassortment during co-infections and contributes to the genetic diversity observed across flyways.

59 BASIC BIOLOGICAL SCIENCES↗

Interpretable machine learning models classify minerals via spectroscopy

Developing methods to identify mineral species confidently and rapidly from Raman spectral analysis is critical to numerous fields. Traditionally, analysis relies on pattern matching the Raman spectrum of an unknown dataset with a supporting library of well-characterized spectral data, which may prove difficult for environmental samples that are poorly crystalline or phase mixtures. Here, we developed interpretable machine learning models that can classify uranium minerals by secondary oxyanion chemistry and other physicochemical properties based solely on Raman spectra. This new ML method produces a mineral profile of physical and chemical properties for an unknown sample and can rapidly classify or identify unknown minerals from Raman data, without the need for an exact pattern match in a spectral library. Training models are validated by 1. Strong correlation of high confidence model regions with published spectroscopic assignments and 2. Correct classification of a mineral not present in training data. Training data are from the Compendium of Uranium Raman and Infrared Experimental Spectra and available crystallographic information files within the open-source Smart Spectral Matching scientific framework. Physically meaningful classifier models can rapidly identify key structural and chemical information about unknown uranium minerals and the overall methodology is broadly applicable for mineral phases.

Machine learning↗

Synthesis and Observation of Emergent Phenomena in Epitaxial Heusler Compound Heterostructures

The proposal was on the synthesis and observation of emergent phenomena in epitaxial Heusler compound heterostructures. The large range of properties and number of Heusler compounds opens up a wide number of potential compounds that will exhibit emergent phenomena. The similarity, large range of relatively inexpensive, large area, high crystal quality, III-V bulk substrates, lattice parameters and the ability to tune the lattice parameters through ternary or quaternary III-V compound semiconductor epitaxial growth, makes III-V semiconductors an ideal choice for substrates for epitaxial growth of Heusler compounds. A number of half Heusler compounds have been predicted to exhibit band inversion, making them topological and are therefore expected to exhibit spin-momentum locked topological surface states with linear dispersion. Others are predicted to be semimetals with Weyl points and others semiconducting and magnetic. During the course of this grant, emphasis has been on investigating Heusler compounds with emergent phenomena and demonstrating the ability to tune their properties through alloying and strain. We have grown toplogical semimetal (PtLuSb, PtMnBi), Weyl (Co 2 MnAl, Co 2 TiGe), half metal (PtMnSb, Co 2 MnSi, Co 2 MnAl x Si 1-x , Co2FeAl), and semiconducting (CoTiSb, NiTiSn) and tuned their properties through alloying and epitaxial strain. We also investigated the closely related materials of rare-earth monopnictide, some of which have also been predicted to be topological. During the attempts to grow the PtMnBi, it was discovered that Bi, another predicted topological material when ultrathin, could be grown epitaxially on InSb, results for which are also reported here. The main focus for this effort has been on using variable photon energy and spin-dependent angle resolved photoemission (ARPES) to determine bulk band structure and surface states of pristine epitaxial films grown on III-V semiconductor and MgO substrates and correlate results with theory and transport measurements. Theory has been critical to interpretation of experimental results and has been essential in guiding experiments. The research benefited from several strong collaborations between the PIs and the beamline scientists at the Advanced Light Source at Lawrence Berkeley Laboratory, the Stanford Linear Accelerator Center (SLAC) at Stanford and at the Max Lab at Lund University in Sweden. The strong experiment - theory collaboration between the PI’s groups, the Palmstrøm group at UCSB and the Janotti group at the University of Delaware, has been critical for interpreting the experimental ARPES and magnetotransport measurements results and making predictions to guide experiments. Weekly interactive Zoom meetings made this work well. A collaboration between the Palmstrøm group and Dr. Alexei Fedorov at the Advanced Light Source (ALS) resulted in significant modifications to his end chamber to accommodate the vacuum suitcase that was designed and constructed in the Palmstrøm group at UCSB. In collaboration with beamline scientists, Drs. Makoto Hashimoto and Donghui Lu at SLAC, Palmstrøm made modifications to the vacuum suitcase and developed special sample holders that allowed samples to be grown in the Palmstrøm MBE systems at UCSB and transported in the UHV vacuum suitcase to SLAC for ARPES measurements. The development of the vacuum suitcase was essential for this grant as it has allowed variable photon energies to be used to identify surface versus bulk states on samples that could not be capped and decapped using As- or Sb-capping layers.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗